Safetensors
GGUF
Turkish
llama
Llama-3
instruct
finetune
chatml
gpt4
synthetic data
distillation
function calling
json mode
axolotl
roleplaying
chat
Instructions to use tda45/TdAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tda45/TdAI with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf tda45/TdAI # Run inference directly in the terminal: ./llama-cli -hf tda45/TdAI
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf tda45/TdAI # Run inference directly in the terminal: ./build/bin/llama-cli -hf tda45/TdAI
Use Docker
docker model run hf.co/tda45/TdAI
- LM Studio
- Jan
- Ollama
How to use tda45/TdAI with Ollama:
ollama run hf.co/tda45/TdAI
- Unsloth Studio
How to use tda45/TdAI with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tda45/TdAI to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tda45/TdAI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tda45/TdAI to start chatting
- Atomic Chat new
- Docker Model Runner
How to use tda45/TdAI with Docker Model Runner:
docker model run hf.co/tda45/TdAI
- Lemonade
How to use tda45/TdAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tda45/TdAI
Run and chat with the model
lemonade run user.TdAI-{{QUANT_TAG}}List all available models
lemonade list
File size: 2,304 Bytes
15c3607 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 | <script lang="ts">
import * as AlertDialog from '$lib/components/ui/alert-dialog';
import { AlertTriangle, TimerOff } from '@lucide/svelte';
import { ErrorDialogType } from '$lib/enums';
interface Props {
open: boolean;
type: ErrorDialogType;
message: string;
contextInfo?: { n_prompt_tokens: number; n_ctx: number };
onOpenChange?: (open: boolean) => void;
}
let { open = $bindable(), type, message, contextInfo, onOpenChange }: Props = $props();
const isTimeout = $derived(type === ErrorDialogType.TIMEOUT);
const title = $derived(isTimeout ? 'TCP Timeout' : 'Server Error');
const description = $derived(
isTimeout
? 'The request did not receive a response from the server before timing out.'
: 'The server responded with an error message. Review the details below.'
);
const iconClass = $derived(isTimeout ? 'text-destructive' : 'text-amber-500');
const badgeClass = $derived(
isTimeout
? 'border-destructive/40 bg-destructive/10 text-destructive'
: 'border-amber-500/40 bg-amber-500/10 text-amber-600 dark:text-amber-400'
);
function handleOpenChange(newOpen: boolean) {
open = newOpen;
onOpenChange?.(newOpen);
}
</script>
<AlertDialog.Root {open} onOpenChange={handleOpenChange}>
<AlertDialog.Content>
<AlertDialog.Header>
<AlertDialog.Title class="flex items-center gap-2">
{#if isTimeout}
<TimerOff class={`h-5 w-5 ${iconClass}`} />
{:else}
<AlertTriangle class={`h-5 w-5 ${iconClass}`} />
{/if}
{title}
</AlertDialog.Title>
<AlertDialog.Description>
{description}
</AlertDialog.Description>
</AlertDialog.Header>
<div class={`rounded-lg border px-4 py-3 text-sm ${badgeClass}`}>
<p class="font-medium">{message}</p>
{#if contextInfo}
<div class="mt-2 space-y-1 text-xs opacity-80">
<p>
<span class="font-medium">Prompt tokens:</span>
{contextInfo.n_prompt_tokens.toLocaleString()}
</p>
{#if contextInfo.n_ctx}
<p>
<span class="font-medium">Context size:</span>
{contextInfo.n_ctx.toLocaleString()}
</p>
{/if}
</div>
{/if}
</div>
<AlertDialog.Footer>
<AlertDialog.Action onclick={() => handleOpenChange(false)}>Close</AlertDialog.Action>
</AlertDialog.Footer>
</AlertDialog.Content>
</AlertDialog.Root>
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